Real-Time Modeling and Registration of Dynamic Geometry

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The augmented reality market is forecast to reach $120 billion by 2020. The advent of consumer-level augmented reality devices (e.g. Microsoft HoloLens) has been fuelled by technological leaps in real-time sensors capable of simultaneously capturing colour and depth (e.g. Microsoft Kinect). While these sensors provide a way of measuring the 3D geometry of the real world, processing geometry in real-time is particularly challenging. For example, many techniques only focus on specific sub-problems like face, body or hand tracking, and thus often assume the object being observed by the camera is of known geometry. Adapting these algorithms to cope with an unknown, dynamic and ever-changing environment is a fundamental challenge, especially when targeting real-time applications with their conflicting requirements of efficiency and power consumption.